In the art, enterprise operators do not typically employ sophisticated analysis to plan operational activity; such as planning promotions, price and inventory allocation in retail, investigating fraudulent claims or pricing policies in insurance, making medical diagnoses, forecasting demand or maintenance for manufacturing, optimizing plant capacity for manufacturing, for example. It is common that enterprises rely on human intuition to interpret overly simplified information to make operational decisions that impact the ultimate performance of enterprise.
Human operators are subject to various influences and effects, including, for instance: (1) personal experience bias, i.e. where personal experiences are not representative samples of the complete decision making experience; (2) fatigue from making a large number of repetitive decisions daily; (3) the need for variety in decision making when no variety necessarily exists; (4) inconsistency in making a decision under the similar or the same enterprise state or environment; (5) an inability to detect change or trends in the enterprise state or environment; (6) the inability to quality control the decisions made; (7) inability to make sense of the overwhelming amount of data generated by enterprise processes; (8) an inability to make decisions in very complex enterprise environments where many factors affect decision outcomes; (10) an inability of a single element of the planning process to take into account all of the interaction effects between all parts of the enterprise and its planning processes; (11) an inability to determine when a system becomes unstable; (12) an inability to detect when a system has had a failure or output has been corrupted. One or more of these factors can lead to sub-optimal enterprise financial and operational performance.
Accordingly, there remains a need for improvements in the art.